BagIQ MCP

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It describes the outputs but not the operation's side-effect profile (e.g., read-only vs. mutating), any required permissions, or limitations such as handling unknown disc names. For an analysis tool, it likely has no side effects, but that is not stated. The description does not go beyond what a user would expect from the name and schema.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, concise sentence that is front-loaded with the core purpose ('complete BagIQ analysis') and then lists the key outputs. There is no filler or redundant information. Every phrase earns its place, making it both efficient and easy to parse.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given that there is no output schema, the description adequately covers the return values by listing slot coverage, bag identity, gaps, overlaps, and flight coordinates. It does not describe error behavior or how invalid disc entries are handled, but the schema covers input constraints (1-35 discs, disc object structure). For a read-only analysis tool, this is reasonably complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so both parameters (discs and preferred_brand) are already well documented in the schema. The description does not add any additional semantic detail about parameters, such as how to format the discs array or that preferred_brand is optional. It provides no value beyond the schema, so the baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states a specific verb+resource: 'Performs a complete BagIQ analysis on a player's disc golf bag.' It enumerates the outputs (slot coverage, identity label, gaps, overlaps, coordinates), making the tool's function obvious. However, it does not explicitly differentiate from sibling tools like find_bag_gaps or detect_overlap, though the 'complete' qualifier hints at broader scope.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no guidance on when to use this tool versus its siblings (build_minimal_bag, detect_overlap, find_bag_gaps, recommend_bag_fillers). The description does not mention conditions for choosing this full analysis over more targeted tools, nor does it state exclusions or alternatives. An agent would have to infer usage from the tool's broad output description.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries full transparency responsibility. It indicates the tool 'extracts' and 'detailing necessary compromises,' which hints at output behavior but does not disclose side effects, constraints, or the fact that target_count range (2..6) differs from the stated '3-to-5.' No contradictions with annotations since none exist.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, well-structured sentence that efficiently communicates the action, input, output goal, and additional output characteristic (compromises). No fluff or redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a straightforward tool with two parameters and no output schema, the description provides sufficient context: it names the input (larger bag), the processing goal (maximize coverage), and output trait (detailing compromises). Minor gap: it doesn't explicitly mention that target_count overrides the default 3-5 range, but this is covered by the schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema provides 100% coverage with detailed descriptions for both discs (including nested object fields) and target_count (with range and default). The description adds no extra parameter-specific meaning, so baseline score of 3 applies per rubric.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's function: 'Extracts an optimal 3-to-5 disc minimalist setup from a larger bag' with explicit goals of 'maximizing shot coverage while detailing necessary compromises.' This distinguishes it from sibling analysis tools like analyze_bag or find_bag_gaps.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies when to use it (to reduce a larger collection to a minimalist setup) but does not explicitly contrast it with siblings. However, the clear purpose and sibling names (analyze, detect, find, recommend) make the appropriate use context readily inferable.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It discloses the tool's behavior: it ranks pairs by overlap severity and recommends which disc to keep or cut. It does not mention any side effects (though it appears read-only), nor does it discuss limitations like handling of locked discs. It covers the core behavior adequately but omits some edge-case handling.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

A single, dense sentence that conveys the tool's purpose, the ranking behavior, and the recommendation outcome with zero fluff. All information is essential and front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (nested objects, enums, and a 'locked' flag that should influence recommendations), the description is incomplete. It does not specify the output format (e.g., list of pairs, severity scores, or recommendation structure) since there is no output schema, nor does it mention how locked discs are handled. An agent calling this tool without further context would be uncertain about the response shape.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents the 'discs' parameter thoroughly, including object structure, enums, and min/max. The description adds no new parameter-level detail beyond implying the input is a list of discs for redundancy analysis. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb ('Detects'), a precise resource ('redundant molds occupying the same flight slot or shot role'), and the resulting actions ('ranking pairs by overlap severity and recommending which disc to keep vs cut'). This clearly differentiates it from siblings like find_bag_gaps (gap identification) or recommend_bag_fillers (additions), so an agent can tell them apart without opening schemas.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for detecting redundancy in a bag and providing cut/keep recommendations. It does not explicitly name alternatives or state when-not-to-use, but the purpose is clear enough that an agent would select it for overlap detection. Missing explicit exclusions, but the context is unambiguous.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool 'identifies' and 'ranks' voids, implying a read-only analysis, but it does not explicitly say whether it modifies the bag or what the return structure looks like beyond a severity ranking. It is not misleading, but it lacks explicit side-effect or output-format transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, tightly worded sentence that front-loads the core purpose and the ranking behavior. There is no filler or redundancy, making it highly efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has one parameter, no output schema, and no annotations. The description adequately conveys the tool's function and the fact that it ranks gaps by severity, which gives a hint about the output. It does not describe the exact output format, but for a simple analysis tool, this is sufficient. The main gap is the lack of explicit side-effect disclosure, but that is covered under behavioral transparency.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema description coverage is 100%, so the parameter 'discs' is fully documented in the schema. The tool description adds no additional parameter semantics beyond what the schema already provides. Baseline 3 is appropriate since the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb ('Identifies'), a clear resource ('missing shot shapes and unserved flight slots'), and the context of BagIQ's 9 core slot targets. It also mentions ranking by severity, which distinguishes it from siblings like detect_overlap (which checks overlaps) and recommend_bag_fillers (which suggests discs). This is a precise, non-tautological purpose.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies the tool is for identifying gaps in a bag, but it does not explicitly state when to use it versus alternatives, nor does it mention exclusions or when not to use it. The context is clear enough for an agent to infer its primary use, but explicit routing to siblings is absent.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It adds useful context by stating the recommendation is based on 'BagIQ matrix coordinates and DiscList ratings,' which explains the underlying logic. However, it does not explicitly state that the operation is read-only, nor does it mention potential edge cases like empty recommendations or handling of locked discs. The description provides some transparency but not a comprehensive behavioral profile.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence that front-loads the primary action and resource. Every word earns its place, with no fluff or repetition. It is concise and efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's moderate complexity (4 parameters, no annotations, no output schema), the description is incomplete. It does not explain the return format or what happens when no gaps exist, nor does it provide any usage guidance relative to sibling tools. The agent is left without information on how to interpret the results or decide when to use this tool instead of find_bag_gaps or build_minimal_bag. The description is too minimal for a tool that likely requires more contextual cues.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema description coverage is 100%, meaning all four parameters are already documented in the schema. The description adds no additional meaning to the parameters; it mentions 'BagIQ matrix coordinates' but that is not a parameter. Per the calibration, a baseline of 3 is appropriate when the schema fully covers parameters and the description adds no extra value.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Suggests the highest-rated discs') and the resource ('to fill missing shot slots or close voids in the bag'). It is specific and distinguishes the tool's purpose from general bag analysis. However, it does not explicitly name any sibling tool to differentiate from, so it stops short of a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies when to use the tool (when there are gaps or voids in the bag) but provides no explicit guidance on when not to use it or how it compares to alternatives like find_bag_gaps or analyze_bag. The usage context is clear but no exclusions or alternatives are given.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.